This project proposes to combine recently highlighted chemical parameters of saliva with more established microbiological assays of plaque and saliva in order to assess the caries-predictive properties of this battery of tests in human populations. Other clinical parameters will also be included, such as Plaque Index scores, fluoride exposure histories, and the covariables examined by Grainger, Lehnoff et al., 1983. The development of such a predictive test will not only aid in directing appropriate treatment to caries-susceptible individuals, but will greatly facilitate larger clinical trials by better enabling investigators to direct their efforts to caries susceptible sub-populations. In addition, data from previous clinical studies will be re-analyzed in an effort to identify factors associated with clinically detectable caries and to devise more efficient means for identifying study subjects and for analyzing data. The specific aims of this project are to: (1) relate clinical caries status to certain chemical and microbiological parameters and identify carious susceptible subjects; (2) improve the selection of study subjects for clinical caries studies by identifying chemical, microbiological and statistical predicators and correlates of dental caries. This study involves collection of additional data from two populations which already exist for other purposes. In addition to DMFS examinations, saliva and plaque will be collected and a questionnaire regarding past and present exposure to fluorides, as well as current dietary and oral hygiene practices, will be administered. Laboratory data collected from saliva will include simulated salivary flow rate, fluoride concentration, S. mutans and lactobacillus counts and presence of specific 12,000 M.W. protein. Plaque will be analyzed for fluoride, calcium, phosphate and organic acid content before and after sucrose challenge. In addition to these laboratory studies, several existing longitudinal clinical trial data bases will be reanalyzed in order to develop methods for more efficient analysis of data.